
name = "Max"
def changeName():
    name = "Niko"
    print(f"name inside the function: {name}")
changeName()
print(f"name outside of the function: {name}")


name = "Max"
def changeName():
    name = "Niko"
    print(f"name inside the function: {name}, address = {id(name)}")
changeName()
print(f"name outside of the function: {name}, address = {id(name)}")


def sum3(a, b, c):
    print(f"a={a}")
    print(f"b={b}")
    print(f"c={c}")
    return a+b+c
sum3(1, 2, 3)


def add(x, y, z=0):
    return x + y + z
print(add(1, 2))
print(add(1, y=2, z=3))


def add(x, y, z=0):
    """
    Calculate the sum of up to three numbers.
    
    Parameters:
    x (int/float): The first number to be added.
    y (int/float): The second number to be added.
    z (int/float, optional): The third number to be added. Defaults to 0 if not provided.
    
    Returns:
    int/float: The sum of the numbers.
    """
    # Return the sum of the provided numbers, z is optional and defaults to 0 if not specified
    return x + y + z

import myMoudle


import pandas as pd
df = pd.DataFrame({
    'name': ['Alice', 'Bob', 'Charlie', 'David'],
    'age': [25, 30, 35, 40],
    'height': [165.4, 175.3, 168.5, 180.6]
})
print(df)
df[df['age'] > 30]


!grep "furniture.*sell" ../downloads/blocket_listings.txt

python retester.py


# Import module
import re


# Define a pattern
p = re.compile('ab*')
p


# Search pattern in string
p = re.compile('ab*')

p.search('abc')


print(p.search('cb'))


p = re.compile('HELLO')
m = p.search('gsdfgsdfgs  HELLO  __!@£§≈[|ÅÄÖ‚…’ﬁ]')

print(m)


# Remember, [a-z]+ matches any lower case english word
p = re.compile('[a-z]+')
result = p.search('ATGAAA')
print(result)


p = re.compile('[a-z]+', re.IGNORECASE)

result = p.search('ATGAAA')
result


p = re.compile('[a-z]+', re.IGNORECASE)

result = p.search('123 ATGAAA 456')
result


result.group()


result.start()


result.end()


result.span()


p = re.compile('.*HELLO.*')


m = p.search('lots of text  HELLO  more text and characters!!! ^^')


m.group()


# Find all instance of the defined pattern
p = re.compile('HELLO')
matches = p.finditer('lots of text  HELLO  more text  HELLO ... and characters!!! ^^')
print(matches)


# Loop through matches
for match in matches:
    print(f'Found {match.group()} at position {match.start()}')


txt = "The first full stop is here: ."
pattern = re.compile('.')

match = pattern.search(txt)
print('"{}" at position {}'.format(match.group(), match.start()))


# Print all matches
matches = p.finditer(txt)
#for match in matches:
#    print('"{}" at position {}'.format(match.group(), match.start()))


# Use escape character to search
p = re.compile('\.')

m = p.search(txt)
print('"{}" at position {}'.format(m.group(), m.start()))


txt = "Do it   becuase   I say so,     not becuase you want!"


# Spell the word because correctly
import re
p = re.compile('becuase')
txt = p.sub('because', txt)
print(txt)


# Remove additional spaces
p = re.compile('\s+')
p.sub(' ', txt)

p = re.compile()

pattern = re.compile( ... )
match = pattern.search('string goes here')
if m:
    print('Match found: ', match.group())
else:
    print('No match')

fh = open('myfile.txt')
for line in fh:
    do_stuff(line)

iterations = 0
information = []

fh = open('myfile.txt', 'r')
for line in fh:
    iterations += 1
    information += do_stuff(line)

str     "hello"
int     5
float   5.2
bool    True

iterations = 0
score = 5.2

+, -, *,...   # mathematical
and, or, not  # logical 
==, !=        # (in)equality
<, >, <=, >=  # comparison
in            # membership


value = 4
nextvalue = 1
nextvalue += value
print('nextvalue: ', nextvalue, 'value: ', value)


x = 5
y = 7
z = 2
x > 6 and y == 7 or z > 1


(x > 6 and y == 7) or z > 1


mystr = "one"


mystr += " two" # string concatnation 
mystr


len(mystr) # get the length


"one" in mystr # membership checking


mystr = "one"
mystr[1] = "W"


mystr = "one"
print(mystr)
mystr = "two"
print(mystr)


mystr = "one"
print(f"mystr = {mystr}, address = {id(mystr)}")
mystr = "two"
print(f"mystr = {mystr}, address = {id(mystr)}")

s.strip()  # remove unwanted spacing

  s.split()  # split line into columns

  s.upper(), s.lower()  # change the case

p = re.compile('A.A.A')
  p.search(dnastring)

  p = re.compile('T')
  p.sub('U', dnastring)


import re

p = re.compile('p.*\sp')  # the greedy star!

p.search('a python programmer writes python code').group()

mylist.append('value')

value in myobj

todolist = ["work", "sleep", "eat", "work"]

todolist.sort()
todolist.reverse()
todolist[2]
todolist[-1]
todolist[2:6]


todolist = ["work", "sleep", "eat", "work"]


todolist.sort()
print(todolist)


todolist.reverse()
print(todolist)


todolist[2]


todolist[-1]


todolist[2:]

mydict = {"a": "alligator", "b": "bear", "c": "cat"}
counter = {"cats": 55, "dogs": 8}

mydict["a"]
mydict.keys()
mydict.values()


counter = {'cats': 0, 'others': 0}

for animal in ['zebra', 'cat', 'dog', 'cat']:
    if animal == 'cat':
        counter['cats'] += 1
    else:
        counter['others'] += 1
        
counter

myset = {"drama", "sci-fi"}

myset.add("comedy")

myset.remove("drama")


todolist = ["work", "sleep", "eat", "work"]

todo_items = set(todolist)
todo_items


todo_items.add("study")
todo_items


todo_items.add("eat")
todo_items

tup = (max_length, sequence)


tup = (2, 'xy')
tup[0]


tup[0] = 2

def find_longest_seq(file):
    # some code here...
    return length, sequence

answer = find_longest_seq(filepath)
print('length', answer[0])
print('sequence', answer[1])

answer = find_longest_seq(filepath) # return as a tuple
length, sequence = find_longest_seq(filepath) # return as two variables

if count > 10:
   print('big')
elif count > 5:
   print('medium')
else:
   print('small')


shopping_list = ['bread', 'egg', ' butter', 'milk']
tired         = True

if len(shopping_list) > 4:
    print('Really need to go shopping!')
elif not tired:
    print('Not tired? Then go shopping!')
else:
    print('Better to stay at home')

information = []
fh = open('myfile.txt', 'r')

for line in fh:
    if is_comment(line):
       use_comment(line)
    else:
       information = read_data(line)

keep_going = True
information = []
index = 0

while keep_going:
    current_line = lines[index]
    information += read_line(current_line)
    index += 1
    if check_something(current_line):
        keep_going = False


user_input = "thank god it's friday"
for letter in user_input:
    print(letter.upper())


i = 0
while i < len(user_input):
    letter = user_input[i]
    print(letter.upper())
    i += 1


user_input = "thank god it's friday"
for letter in user_input:

    if letter == 'd':
        break
    print(letter.upper())


# DON'T RUN THIS
i = 0
-while i < 10:    
    print(user_input[i])

fh = open(filename, 'r')
   for line in fh:
       fh.read()
       fh.readlines()

fh.close()

def prettyprinter(name, value, delim=":", end=None):
    out = "The " + name + " is " + delim + " " + value
    if end:
        out += end
    return out

""" This is a doc-string explaining what the purpose of this function/module is """

Introduction to¶

with Application to Bioinformatics¶

- Day 5¶

Day 5¶

Quiz: Review Day 4¶

1. What happens if you declare a variable with the same name inside and outside a function?¶

2. What is the difference between positional arguments and keyword arguments?¶

Arguments can be used in both ways, with or without keyword, if there is no ambiguity¶

3. What will be the output of the following code snippet?¶

4. Why is it beneficial to use docstrings in functions?¶

Both """ and ''' can be used for docstring¶

5. How can you see the documentation of a Python library function in the console?¶

6. Which of these import statements would avoid a name conflict if there’s a local variable math in the same script?¶

7. What will happen if you import the same module multiple times in a Python script?¶

8. If you want to filter rows in df where age is greater than 30, which command would you use?¶

9. If you want to rename multiple columns in a DataFrame df, which method should you use?¶

New topic: Regular Expressions¶

Examples where regex can play a role¶

Regex is not unique for Python and it is supported by¶

Defining a search pattern¶

More common operations - classes of characters¶

More common operations - classes of characters¶

More common operations - classes of characters¶

More common operations - classes of characters¶

More common operations - classes of characters¶

Example - finding patterns in a VCF file¶

Cheat sheet¶

Day 5, Exercise 1 (~30 min)¶

Practicing regular expressions¶

Take a break after the exercise (~10 min)¶

Session 2¶

Regular expressions in Python¶

Searching¶

Case insensitiveness¶

The match object¶

Zero or more...?¶

Finding all the matching patterns¶

How to find a full stop?¶

More operations¶

Substitution¶

Finally, we can fix our spelling mistakes!¶

Overview¶

Summary¶

Day 5, Exercise 2 (~30 min)¶

Use regular expressions with Python¶

Take a break after the exercise (~10 min)¶

PyQuiz 5.1 (~10 min)¶

Lunch¶

Sum up!

Processing files - looping through the lines¶

Store values¶

Values¶

Assign values¶

Compare and membership¶

Strings¶

String is immutable¶

String manipulation¶

Regular expressions help you find and replace strings.¶

Collections¶

Collections¶

Lists¶

Dictionaries¶

Sets¶

Tuples¶

Tuples in functions¶

Deciding what to do with if else statement¶

Deciding what to do - if statement¶

Program flow - for loops¶

Program flow - while loops¶

Different types of loops¶

Controlling loops¶

File Input/Output¶

Input/Output¶

Code structure¶

Functions¶

Functions - keyword arguments¶

Using your code¶

Documentation and comments¶

Why programming?¶

Why programming?¶

Both `"""` and `'''` can be used for docstring¶

6. Which of these import statements would avoid a name conflict if there’s a local variable `math` in the same script?¶

8. If you want to filter rows in `df` where `age` is greater than 30, which command would you use?¶

9. If you want to rename multiple columns in a DataFrame `df`, which method should you use?¶